摘要
生产系统优化改善是企业的永恒问题,过去由于条件限制,企业大多凭经验进行优化改善,无法做到改善的全面化、系统化、有目标的进行.在大数据背景下,通过大数据分析包括机器学习、数据挖掘、统计、优化和数字孪生等技术方法,分析生产系统中存在的各种问题从而找到全局优化点以及明确的改善点,将使企业快速完善生产系统,从而提高竞争力.对已有的基于大数据的生产系统研究进行了分类归纳总结,主要从质量改善、生产调度与安排、流程优化和供应链决策支持等方面进行系统综述,为进一步研究提供参考.
Optimization and improvement of production system is an eternal problem of enterprises.In the past,due to the limitations of conditions,enterprises mostly carried out optimization and improvement by experience,and could not achieve comprehensive,sys-tematic and targeted improvement.In the context of big data,through big data analysis including machine learning,data mining,statistics,optimization and digital twinning and other technical methods,analyze various problems existing in the production system to find global optimization points and clear improvement points,will enable enterprises to quickly improve the production system,so as to improve competitiveness.This paper classifies and summarizes the existing research on production system based on big data,mainly from the aspects of quality improvement,production scheduling and arrangement,process optimiza-tion and supply chain decision support,etc.,to provide reference for further research.
作者
徐峰
张彦雨
龚其国
XU Feng;ZHANG Yan-yu;GONG Qi-guo(School of Economics and Management,UCAS,Beijing 100190,China)
出处
《数学的实践与认识》
2022年第12期279-292,共14页
Mathematics in Practice and Theory
关键词
大数据
数据挖掘
机器学习
生产系统
优化
bigdata
data mining
machine learning
production systems
optimization